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Stomach Neoplasms

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Machine learning algorithms able to predict the prognosis of gastric cancer patients treated with immune checkpoint inhibitors.

World journal of gastroenterology
BACKGROUND: Although immune checkpoint inhibitors (ICIs) have demonstrated significant survival benefits in some patients diagnosed with gastric cancer (GC), existing prognostic markers are not universally applicable to all patients with advanced GC.

Advances in artificial intelligence for predicting complication risks post-laparoscopic radical gastrectomy for gastric cancer: A significant leap forward.

World journal of gastroenterology
In a recent paper, Hong developed an artificial intelligence (AI)-driven predictive scoring system for potential complications following laparoscopic radical gastrectomy for gastric cancer patients. They demonstrated that integrating AI with random ...

Expression of Salivary miRNAs, Clinical, and Demographic Features in the Early Detection of Gastric Cancer: A Statistical and Machine Learning Analysis.

Journal of gastrointestinal cancer
OBJECTIVE: Gastric cancer ranks as one of the top five deadliest cancers worldwide and is often diagnosed at late stages. Analysis of saliva may provide a non-invasive approach for detection of malignancies in organs associated with the oral cavity. ...

Accuracy of machine learning in diagnosing microsatellite instability in gastric cancer: A systematic review and meta-analysis.

International journal of medical informatics
BACKGROUND: Significant challenges persist in the early identification of microsatellite instability (MSI) within current clinical practice. In recent years, with the growing utilization of machine learning (ML) in the diagnosis and management of gas...

Random survival forest algorithm for risk stratification and survival prediction in gastric neuroendocrine neoplasms.

Scientific reports
This study aimed to construct and assess a machine-learning algorithm designed to forecast survival rates and risk stratification for patients with gastric neuroendocrine neoplasms (gNENs) after diagnosis. Data on patients with gNENs were extracted a...

A deep learning approach for gastroscopic manifestation recognition based on Kyoto Gastritis Score.

Annals of medicine
OBJECTIVE: The risk of gastric cancer can be predicted by gastroscopic manifestation recognition and the Kyoto Gastritis Score. This study aims to validate the applicability of AI approaches for recognizing gastroscopic manifestations according to th...

Transformative artificial intelligence in gastric cancer: Advancements in diagnostic techniques.

Computers in biology and medicine
Gastric cancer represents a significant global health challenge with elevated incidence and mortality rates, highlighting the need for advancements in diagnostic and therapeutic strategies. This review paper addresses the critical need for a thorough...

Prognostic insights after surgery for advances in understanding signet ring cell gastric cancer: a machine learning approach.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
BACKGROUND: Signet ring cell (SRC) gastric carcinoma is traditionally associated with a poor prognosis. However, the literature has presented contradictory results. Linear models are the standard statistical tools typically used to study these condit...

Development and validation of a machine-learning model for preoperative risk of gastric gastrointestinal stromal tumors.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
BACKGROUND: Gastrointestinal stromal tumors (GISTs) have malignant potential, and treatment varies according to risk. However, no specific protocols exist for preoperative assessment of the malignant potential of gastric GISTs (gGISTs). This study ai...